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Abstract

The heterogeneous-based 4G wireless networks will offer noticeable advantages for both users and network operators. The users will benefit from the vibrant coverage and capacity. A vast number of available resources will allow them to connect seamlessly to the best available access technology. The network operators, on the other hand, will be benefited from the lower cost and the efficient usage of the network resources. However, managing QoS for video or voice applications over these networks is still a challenging task. In this chapter, a generalized metric-based approach is described for QoS quantification in Heterogeneous networks. To investigate the efficiency of the designed approach, a range of simulation studies based on different models of service over the heterogeneous networks are carried out. The simulation results indicate that the proposed approach facilitates better management and monitoring of heterogeneous network configurations and applications utilizing them.

Introduction

A heterogeneous communication network provides transparent and self-configurable services across wireless local area networks (WLANs), Wireless Metropolitan Area Networks (WMANs) and Wireless wide area networks (WWANs). Primarily, heterogeneous networks were visioned as an integration of IEEE 802.11 WLANs and 3G/2.5G/2G/B3G all these cellular technologies, mobile WiMAX being the major player in the middle. However, the recent advancement of LTE-advance has added one more new technology in the picture, which would play a fundamental role in this integrated architecture and will form the 4th generation (4G) or next-generation of wireless networks. The heterogeneous wireless access, the exclusive all IP-based architecture and the advanced mobility support are the key drivers of this generation (Hossain, 2008).

All the technologies, which are behind the heterogeneous networks poses the characteristics that complement each other (Zahran, Liang, & Saleh, 2006). 3G and 2G-based cellular communication technologies are well-known for wide area coverage, complete mobility, and roaming. However, traditionally these technologies offer low bandwidth, and expensive data traffic solutions (Chalmers, Krishnamurthi, & Almeroth, 2006). LTE technology is developed in response to overcoming the limitations of the conventional cellular technologies. On the other hand, WLANs provide high data rate at low cost, but with limited coverage, whereas WiMAX delivers last mile mobile broadband access and backhaul for WLANs (Fangmin, Luyong, & Zheng, 2007).

Hence, from network designing, planning, and troubleshooting perspectives, a QoS evaluation method is required that can bring these domains into a common platform. Generally speaking, the key performance parameters for these technologies are not directly comparable. For example, the delay ranges of UMTS and WLAN are entirely different. Therefore, a high value of delay measured from a WLAN may not be considered elevated in a UMTS environment. On the other hand, the applications running over them have the same QoS characteristics regardless of the communication technology they are utilizing. Hence, in this context, an application-based QoS evaluation approach is more applicable than a communication technology-based performance evaluation approach. The most current studies aim to evaluate the QoS of each application or radio access network individually. This method is useful in case of networks that use one type of communication technology. However, for heterogeneous networks, the presence of multiple types of applications and access technologies make the assessment of the overall performance challenging.

This chapter proposes a generalized metric based QoS evaluation method to unify multiple performance evaluation parameters into a single measurement metric. The metrics measure the performance of different entities in a network such as applications and radio access networks (RANs) and represent the measurement with a single value. This approach is evaluated using various simulation scenarios. The particular focus is on multimedia-based applications such as video conferencing (VC), video streaming (VS) and voice. These applications have distinct characteristics, necessitating special attention to their QoS evaluation methods.